• Dr T.Jyothirmayi
• B.Soujanya
• G.L.Aruna Kumari

Road accidents are uncertain and unpredictable. Many factors includeing type of vehicle, road type, lighting on road, road feature, etc contribute to different types of road accidents. Here in this proposed work the road accident information which has been collected for a period of time in a particular area is observed and analyzes the cause of the accidents by different algorithms possible, and try to reduce the occurrences of the accidents in future. This model also helps traffic engineers to know the information related to accidents and places where they occurred frequently and help them to make necessary changes in the infrastructure. Here one of the classification techniques called Support Vector Machine (SVM) is used in order to classify the data. Support Vector Machine uses kernels, which can build in expert knowledge about the problem via engineering the kernels. The prediction of future instances is done with the help of classification model. This model with some further enhancements will be useful for the road engineers to focus and develop new approaches for reducing the road accidents.

Support Vector Machine, classification, Road Traffic Accident

"ANALYZING ROAD ACCIDENT DATA USING CLASSIFICATION TECHNIQUE", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 6, page no.228-232, June-2019, Available :http://www.jetir.org/papers/JETIR1906958.pdf

"ANALYZING ROAD ACCIDENT DATA USING CLASSIFICATION TECHNIQUE", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 6, page no. pp228-232, June-2019, Available at : http://www.jetir.org/papers/JETIR1906958.pdf